26/02/2021

Full time PhD (3 years) on Human integration to manufacturing control system

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  • ORGANISATION NAME
    CRAN (University of Lorraine and CNRS)
  • ORGANISATION COUNTRY
    France
  • FUNDING TYPE
    Funding
  • DEADLINE DATE
    16/04/2021
  • RESEARCH FIELD
    Professions and applied sciences
  • CAREER STAGE
    First Stage Researcher (R1) (Up to the point of PhD)

Description

Funding : Phd Funding

Title:

Human integration to manufacturing control system : human factors, socio-cultural inspired interactions

Dates:

2021/10/01 - 2024/09/30

Supervisor(s): 

Hind BRIL-EL HAOUZI , Guillaume DEMESURE

Description:

The changing nature of industrial requirements brings with it extensive new studies in manufacturing systems

where reactivity in the short term and adaptability to market changes in the long term become increasingly

demanded. To cover these new requirements, some efforts in manufacturing control have been paid to

propose hybrid control architecture and methodologies, where distributed artificial intelligence plays an

essential role (Cardin et al., 2017). For this purpose, the industry for the future paradigm brings technological

advancement due to Information and Communication Technologies (ICT), as well as to advancement in

distributed computer sciences. The advancement from Industry 4.0 aims to face the evolution of customer

needs, in terms of reactivity and performances. However, in spite of technological evolution, the

implementation of hybrid control in industry remains a complex challenge. This complexity is mainly due to the

human, which, in one hand, is excluded in the design of control methodologies, and in the other hand, does

not accept the technology (Bril El-Haouzi, 2017).

This thesis aims to propose a new design approach of manufacturing control, which consider the human in the

system. This approach, called "anthropocentric", is based on the assumption, proved by several researches in

anthropology ( ), that human better accepts the technology within its environment, if this technology

behaves and communicates similarly as him. These researches on anthropocentric approaches have started on

two previous thesis frameworks. The first one focused on the design of human-inspired control algorithms

such as negotiation or consensus (Mezgebe et al., 2019). The second one focused on the social relationships,

where a meta-model have been proposed. This meta-model leads to a new paradigm, called "Internet of Social

Agents (IoSA)", where each entity (i.e. agent) of the network can be an object (IoT) or a human (Valette et al,

2020).

The originality of the proposed thesis is the design of manufacturing control, by considering both the human

factors and the social aspect from IoSA paradigm. The first phase of the design leads the modeling of an agent

(state, dynamic, decisions), which will integrate both human (e.g. physical and mental conditions) and social

(interaction with others) dimensions. For applicability purpose, we will focus on the scheduling problem, which

is well known in the literature and a focus in manufacturing control. In scheduling problems, human factors

(e.g. fatigue) are seldom investigated, since they bring a high complexity related to human variability

(individual characteristics, heterogeneity) as well as the human unpredictability (human errors). Furthermore,

the link between human factors and scheduling is a challenge, since scheduling depends on human factors,

depending themselves on a proposed schedule.

In order to consider these human factors, the proposed agent model, based on discrete event state model, will

integrate some states related to human factors, evolving in short (fatigue), mid (cognitive charge) and long

(mood) time horizon. These states will evolve according to the predefined schedule, i.e. according to the

sequence of actions computed during the decision-making process. The decision making process will use the

state, including the human factors, as in state feedback control. In order to observe the human factors' states,

predictive methods (which can be from artificial intelligence) will be used to estimate the factors, by using

other measured states such as the efficiency (or lack of efficiency) of the actions performed by the agent.

In order to show the applicability of proposed methods, the flexible manufacturing cell "TRACILOGIS" will be

used.

Keywords:

Internet of Social Agents, Intelligent manufacturing control, Human factors

Conditions:

The duration of the thesis will be 3 years funded by a doctoral contract from the University of Lorraine

the remuneration is that of a classical doctoral contract

Thesis carried out at CRAN

Expected profile:

- Master in computer engineering, industrial engineering, automatic

- Goof level of written and oral English

Department(s): 

Eco-Technic systems engineering

 

 

Disclaimer:

The responsibility for the funding offers published on this website, including the funding description, lies entirely with the publishing institutions. The application is handled uniquely by the employer, who is also fully responsible for the recruitment and selection processes.